Removal of Cyclic Borehole Noise From Low- and High-Resolution LWD Images and Its Impact on Image Interpretation
- Junichi Sugiura (Schlumberger) | Rick Lee (PathFinder, a Schlumberger company)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- August 2012
- Document Type
- Journal Paper
- 462 - 472
- 2012. Society of Petroleum Engineers
- 3.3.2 Borehole Imaging and Wellbore Seismic, 1.6 Drilling Operations, 5.6.1 Open hole/cased hole log analysis, 1.12.2 Logging While Drilling
- 1 in the last 30 days
- 568 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
The use of logging-while-drilling (LWD) imaging tools in real-time decision making and post-drilling analysis has become commonplace. However, image noise and processing errors because of inherent measurement physics can propagate errors and, thus, complicate interpretation of openhole log data and images. For example, standard density images tend to amplify image noise from small borehole irregularities. Among different borehole irregularities, spiraling is known to occur more frequently with conventional rotary assemblies, steerable motor assemblies, and rotary-steerable assemblies. When the cyclic-noise amplitude from spiraling becomes large relative to the measurement of the primary interest, it grossly affects the quality of the recorded formation bulk density, photoelectric factor, and neutron porosity.
This paper shows novel methods to remove cyclic noise from formation-evaluation (FE) images by applying frequency-domain filtering. Although the initial attempt of fast Fourier transforms (Zhang et al. 2010) illustrates the straightforward concept, it is seldom used because of implementation issues requiring interactive filter design and intensive operator intervention. Recently, a new method (Sugiura et al. 2011) has been designed to improve the filtering process. Additionally, the new adaptive filter designs automate the cyclic-noise-removal process from the FE images. Standalone software has been developed to process the entire image logs from one well, without human supervision. The software adaptively modifies the filter behavior as borehole-oscillation noise characteristics change with formation, drilling assemblies, hole inclination, and depth.
To examine its validity qualitatively, the algorithm is then applied to various field data, not only on low-resolution density images but also on higher-resolution density images. The new algorithm has been proved by bringing considerable improvement to the image quality without any artificial interruptions. The rugosity effect is reduced significantly, and the apparent resolution of bed-boundary features is increased.
Furthermore, comparative field examples illustrate the improvement in image-feature extraction. The method described here is critical, for example, for small-fracture detection and more-precise definition of formation-property contrasts indicative of bed boundaries in irregular boreholes. This new method not only is effectively used for density images but also is applicable to any other borehole images, such as resistivity and ultrasonic images.
|File Size||18 MB||Number of Pages||11|
Aadnoy, B.S. 1990. In-situ stress directions from borehole fracture traces.J. Pet. Sci. Eng. 4 (2): 143-153. http://dx.doi.org/10.1016/0920-4105(90)90022-u.
Ahmed, N., Natarajan, T., and Rao, K.R. 1974. Discrete Cosine Transform.IEEE Trans. Comput. C-23 (1): 90-93. http://dx.doi.org/10.1109/T-C.1974.223784.
Barton, C.A., Moos, D., Peska, P. et al. 1997. Utilizing wellbore image datato determine the complete stress tensor: application to permeability anisotropyand wellbore stability. The Log Analyst 38: 21-33.
Barton, C., Moos, D., and Tezuka, K. 2009. Geomechanical wellbore imaging:Implications for reservoir fracture permeability. AAPG Bull. 93 (11): 1551-1569. http://dx.doi.org/10.1306/06180909030.
Bourke, L.T. and Prosser, D.J. 2010. An independent comparison of boreholeimaging tools and their geological interpretability. Paper presented at theSPWLA 51st Annual Logging Symposium, Perth, Australia, 19-23 June.
Bovik, A. ed. 2000. Handbook of Image & Video Processing, Sec.II, 53-67. San Diego, California: Academic Press.
Evans, M., Best, D., Holenka, J. et al. 1995. Improved Formation EvaluationUsing Azimuthal Porosity Data While Drilling. Paper SPE 30546 presented at theSPE Annual Technical Conference and Exhibition, Dallas, 22-25 October. http://dx.doi.org/10.2118/30546-MS.
Fitz, D.E. and Mills, A.A. 2003. Cyclic Noise in Open-hole and Cased-holeLogging Measurements: Its Impact and Remediation. Paper SPE 84203 presented atthe SPE Annual Technical Conference and Exhibition, Denver, 5-8 October. http://dx.doi.org/10.2118/84203-MS.
Hurley, N.F., Thorn, D.R., Carlson, J.L. et al. 1994. Using borehole imagesfor target-zone evaluation in horizontal wells. AAPG Bull. 78 (2): 238-247.
Hurley, N.F. 2004. Borehole Images. In Basic Well Log Analysis, ed.G. Asquith and D. Krygowski, No. 16, 151-164. Tulsa, Oklahoma: Methods inExploration Series, AAPG.
Lagraba, P.J.O., Hansen, S.M., Spalburg, M. et al. 2010. Borehole image tooldesign, value of information, and tool selection. In Dipmeter And BoreholeImage Log Technology, ed. M. Poppelreiter, C. Garcia-Carballido, and K. M.,No. 92, 15-38. Tulsa, Oklahoma: AAPG Memoir, American Association of PetroleumGeologists.
Lofts, J.C., Bedford, J., Boulton, H. et al. 1997. Feature recognition andthe interpretation of images acquired from horizontal wellbores. InDevelopments in Petrophysics, ed. M.A. Lovell and P.K. Harvey, No.122,345-365. Bath, UK: Special Publication, The Geological Society PublishingHouse.
Ma, T.A., Lincecum, V., Reinmiller, R. et al. 1993. Natural and inducedfracture classification using image analysis. Paper 1993-J presented at theSPWLA 34th Annual Logging Symposium, Calgary, 13-16 June.
Meyer, N., Holehouse, S., Kirkwood, A. et al. 2005. Improved LWD densityimages and their handling for thin bed definition and for hole shapevisualization. Paper 2005-Y presented at the SPWLA 46th Annual LoggingSymposium, New Orleans, 26-29 June.
Nieto, J.A., Schmitt, D.P., and Keys, R.G. 1995a. Removal of BoreholeInduced Noise from Well Logs. Paper 1995-III presented at the SPWLA 36th AnnualLogging Symposium, Paris, 26-29 June.
Nieto, J.A., Schmitt, D.P., Keys, R.G. et al. 1995b. Method for RemovingBorehole Rugosity Noise from Well Log Data. US Patent No. 5,579,248.
Perkins, T., Quirein, J.A., and Parker, T.J. 2009. Wireline and LWD BoreholeImage Log Dip and Azimuth Uncertainty. Paper SPWLA-2009-21847 presented at theSPWLA 50th Annual Logging Symposium, The Woodlands, Texas, USA, 21-24 June.
Prensky, S.E. 1999. Advances in borehole imaging technology andapplications. In Borehole Imaging: Applications and Case Histories, ed.M.A. Lovell, G. Willamson, and P.K. Harvey, No. 159, 1-44. London: SpecialPublication, The Geological Society Publishing House.
Sugiura, J. and Jones, S. 2008. The Use of the Industry's First 3DMechanical Caliper Image While Drilling Leads to Optimized Rotary SteerableDrilling Assemblies in Push and Point-the-Bit Configurations. Paper SPE 115395presented at the SPE Annual Technology Conference and Exhibition, Denver, 21-24September. http://dx.doi.org/10.2118/115395-MS.
Sugiura, J. 2009a. Improving Rotary-Steerable Borehole Quality UsingInnovative Imaging Techniques. Paper OTC 19991 presented at the OffshoreTechnology Conference, Houston, 4-7 May. http://dx.doi.org/10.4043/19991-MS.
Sugiura, J. 2009b. Novel Mechanical Caliper Image While Drilling andBorehole Image Analysis. Paper SPWLA-2009-49451 presented at the SPWLA 50thAnnual Logging Symposium, The Woodlands, Texas, USA, 21-24 June.
Sugiura, J. 2009c. Probablistic imaging with azimuthally sensitive MWD/LWDsensors. US Patent No. 7,558,675.
Sugiura, J. 2011a. Cyclic Noise Removal in Borehole Imaging. US PatentApplication No. 20110038559 (A1).
Sugiura, J. 2011b. Improved LWD Density Images in the Presence of CyclicBorehole Noise. Paper AADE-11-NTCE-66 presented at the 2011 National TechnicalConference and Exhibition, Houston, 12-14 April.
Sugiura, J. and Jones, S. 2011. Closed-loop physical caliper measurementsand directional drilling method. US Patent No. 7,967,081.
Zhang, J., Boonen, P., and Liu, Z. 2010. Cyclic Noise Removal in BoreholeImaging. US Patent Application No. 20100322533 (A1).
Zoback, M.D., Moos, D., Mastin, L. et al. 1985. Well bore breakouts andin-situ stress. J. Geophys. Res. 90 (B7): 5523-5530. http://dx.doi.org/10.1029/JB090iB07p05523.